Change TrainingArgs -> TrainerArgs

TTS/bin/train_tts.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config import load_config, register_config
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.datasets import load_tts_samples
 from TTS.tts.models import setup_model
 
@@ -9,7 +9,7 @@ from TTS.tts.models import setup_model
 def main():
     """Run `tts` model training directly by a `config.json` file."""
     # init trainer args
-    train_args = TrainingArgs()
+    train_args = TrainerArgs()
     parser = train_args.init_argparse(arg_prefix="")
 
     # override trainer args from comman-line args

TTS/bin/train_vocoder.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config import load_config, register_config
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.utils.audio import AudioProcessor
 from TTS.vocoder.datasets.preprocess import load_wav_data, load_wav_feat_data
 from TTS.vocoder.models import setup_model
@@ -10,7 +10,7 @@ from TTS.vocoder.models import setup_model
 def main():
     """Run `tts` model training directly by a `config.json` file."""
     # init trainer args
-    train_args = TrainingArgs()
+    train_args = TrainerArgs()
     parser = train_args.init_argparse(arg_prefix="")
 
     # override trainer args from comman-line args

recipes/ljspeech/align_tts/train_aligntts.py

@@ -1,6 +1,6 @@
 import os
 
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.align_tts_config import AlignTTSConfig
 from TTS.tts.configs.shared_configs import BaseDatasetConfig
 from TTS.tts.datasets import load_tts_samples
@@ -57,7 +57,7 @@ model = AlignTTS(config, ap, tokenizer)
 # Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
 # distributed training, etc.
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 
 # AND... 3,2,1... 🚀

recipes/ljspeech/fast_pitch/train_fast_pitch.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config.shared_configs import BaseAudioConfig, BaseDatasetConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.fast_pitch_config import FastPitchConfig
 from TTS.tts.datasets import load_tts_samples
 from TTS.tts.models.forward_tts import ForwardTTS
@@ -90,6 +90,6 @@ model = ForwardTTS(config, ap, tokenizer, speaker_manager=None)
 
 # init the trainer and 🚀
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 trainer.fit()

recipes/ljspeech/fast_speech/train_fast_speech.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config import BaseAudioConfig, BaseDatasetConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.fast_speech_config import FastSpeechConfig
 from TTS.tts.datasets import load_tts_samples
 from TTS.tts.models.forward_tts import ForwardTTS
@@ -89,6 +89,6 @@ model = ForwardTTS(config, ap, tokenizer)
 
 # init the trainer and 🚀
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 trainer.fit()

recipes/ljspeech/glow_tts/train_glowtts.py

@@ -2,7 +2,7 @@ import os
 
 # Trainer: Where the ✨️ happens.
 # TrainingArgs: Defines the set of arguments of the Trainer.
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 
 # GlowTTSConfig: all model related values for training, validating and testing.
 from TTS.tts.configs.glow_tts_config import GlowTTSConfig
@@ -72,7 +72,7 @@ model = GlowTTS(config, ap, tokenizer, speaker_manager=None)
 # Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
 # distributed training, etc.
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 
 # AND... 3,2,1... 🚀

recipes/ljspeech/hifigan/train_hifigan.py

@@ -1,6 +1,6 @@
 import os
 
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.utils.audio import AudioProcessor
 from TTS.vocoder.configs import HifiganConfig
 from TTS.vocoder.datasets.preprocess import load_wav_data
@@ -40,7 +40,7 @@ model = GAN(config)
 
 # init the trainer and 🚀
 trainer = Trainer(
-    TrainingArgs(),
+    TrainerArgs(),
     config,
     output_path,
     model=model,

recipes/ljspeech/multiband_melgan/train_multiband_melgan.py

@@ -1,6 +1,6 @@
 import os
 
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.utils.audio import AudioProcessor
 from TTS.vocoder.configs import MultibandMelganConfig
 from TTS.vocoder.datasets.preprocess import load_wav_data
@@ -40,7 +40,7 @@ model = GAN(config)
 
 # init the trainer and 🚀
 trainer = Trainer(
-    TrainingArgs(),
+    TrainerArgs(),
     config,
     output_path,
     model=model,

recipes/ljspeech/speedy_speech/train_speedy_speech.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config import BaseAudioConfig, BaseDatasetConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.speedy_speech_config import SpeedySpeechConfig
 from TTS.tts.datasets import load_tts_samples
 from TTS.tts.models.forward_tts import ForwardTTS
@@ -75,7 +75,7 @@ model = ForwardTTS(config, ap, tokenizer)
 # Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
 # distributed training, etc.
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 
 # AND... 3,2,1... 🚀

recipes/ljspeech/tacotron2-DCA/train_tacotron_dca.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config.shared_configs import BaseAudioConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.shared_configs import BaseDatasetConfig
 from TTS.tts.configs.tacotron2_config import Tacotron2Config
 from TTS.tts.datasets import load_tts_samples
@@ -88,7 +88,7 @@ model = Tacotron2(config, ap, tokenizer)
 # Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
 # distributed training, etc.
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 
 # AND... 3,2,1... 🚀

recipes/ljspeech/tacotron2-DDC/train_tacotron_ddc.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config.shared_configs import BaseAudioConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.shared_configs import BaseDatasetConfig
 from TTS.tts.configs.tacotron2_config import Tacotron2Config
 from TTS.tts.datasets import load_tts_samples
@@ -83,7 +83,7 @@ model = Tacotron2(config, ap, tokenizer, speaker_manager=None)
 
 # init the trainer and 🚀
 trainer = Trainer(
-    TrainingArgs(),
+    TrainerArgs(),
     config,
     output_path,
     model=model,

recipes/ljspeech/univnet/train.py

@@ -1,6 +1,6 @@
 import os
 
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.utils.audio import AudioProcessor
 from TTS.vocoder.configs import UnivnetConfig
 from TTS.vocoder.datasets.preprocess import load_wav_data
@@ -39,7 +39,7 @@ model = GAN(config)
 
 # init the trainer and 🚀
 trainer = Trainer(
-    TrainingArgs(),
+    TrainerArgs(),
     config,
     output_path,
     model=model,

recipes/ljspeech/vits_tts/train_vits.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config.shared_configs import BaseAudioConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.shared_configs import BaseDatasetConfig
 from TTS.tts.configs.vits_config import VitsConfig
 from TTS.tts.datasets import load_tts_samples
@@ -33,7 +33,7 @@ audio_config = BaseAudioConfig(
 config = VitsConfig(
     audio=audio_config,
     run_name="vits_ljspeech",
-    batch_size=16,
+    batch_size=32,
     eval_batch_size=16,
     batch_group_size=5,
     num_loader_workers=0,
@@ -48,8 +48,7 @@ config = VitsConfig(
     compute_input_seq_cache=True,
     print_step=25,
     print_eval=True,
-    mixed_precision=False,
+    mixed_precision=True,
-    max_seq_len=500000,
     output_path=output_path,
     datasets=[dataset_config],
 )
@@ -76,7 +75,7 @@ model = Vits(config, ap, tokenizer, speaker_manager=None)
 
 # init the trainer and 🚀
 trainer = Trainer(
-    TrainingArgs(),
+    TrainerArgs(),
     config,
     output_path,
     model=model,

recipes/ljspeech/wavegrad/train_wavegrad.py

@@ -1,6 +1,6 @@
 import os
 
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.utils.audio import AudioProcessor
 from TTS.vocoder.configs import WavegradConfig
 from TTS.vocoder.datasets.preprocess import load_wav_data
@@ -37,7 +37,7 @@ model = Wavegrad(config)
 
 # init the trainer and 🚀
 trainer = Trainer(
-    TrainingArgs(),
+    TrainerArgs(),
     config,
     output_path,
     model=model,

recipes/ljspeech/wavernn/train_wavernn.py

@@ -1,6 +1,6 @@
 import os
 
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.utils.audio import AudioProcessor
 from TTS.vocoder.configs import WavernnConfig
 from TTS.vocoder.datasets.preprocess import load_wav_data
@@ -39,7 +39,7 @@ model = Wavernn(config)
 
 # init the trainer and 🚀
 trainer = Trainer(
-    TrainingArgs(),
+    TrainerArgs(),
     config,
     output_path,
     model=model,

recipes/multilingual/vits_tts/train_vits_tts.py

@@ -2,7 +2,7 @@ import os
 from glob import glob
 
 from TTS.config.shared_configs import BaseAudioConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.shared_configs import BaseDatasetConfig
 from TTS.tts.configs.vits_config import VitsConfig
 from TTS.tts.datasets import load_tts_samples
@@ -119,7 +119,7 @@ model = Vits(config, speaker_manager, language_manager)
 
 # init the trainer and 🚀
 trainer = Trainer(
-    TrainingArgs(),
+    TrainerArgs(),
     config,
     output_path,
     model=model,

recipes/vctk/fast_pitch/train_fast_pitch.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config import BaseAudioConfig, BaseDatasetConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.fast_pitch_config import FastPitchConfig
 from TTS.tts.datasets import load_tts_samples
 from TTS.tts.models.forward_tts import ForwardTTS
@@ -85,7 +85,7 @@ model = ForwardTTS(config, ap, tokenizer, speaker_manager=speaker_manager)
 # Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
 # distributed training, etc.
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 
 # AND... 3,2,1... 🚀

recipes/vctk/fast_speech/train_fast_speech.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config import BaseAudioConfig, BaseDatasetConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.fast_speech_config import FastSpeechConfig
 from TTS.tts.datasets import load_tts_samples
 from TTS.tts.models.forward_tts import ForwardTTS
@@ -83,7 +83,7 @@ model = ForwardTTS(config, ap, tokenizer, speaker_manager=speaker_manager)
 # Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
 # distributed training, etc.
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 
 # AND... 3,2,1... 🚀

recipes/vctk/glow_tts/train_glow_tts.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config.shared_configs import BaseAudioConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.glow_tts_config import GlowTTSConfig
 from TTS.tts.configs.shared_configs import BaseDatasetConfig
 from TTS.tts.datasets import load_tts_samples
@@ -83,7 +83,7 @@ model = GlowTTS(config, ap, tokenizer, speaker_manager=speaker_manager)
 # Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
 # distributed training, etc.
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 
 # AND... 3,2,1... 🚀

recipes/vctk/speedy_speech/train_speedy_speech.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config import BaseAudioConfig, BaseDatasetConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.speedy_speech_config import SpeedySpeechConfig
 from TTS.tts.datasets import load_tts_samples
 from TTS.tts.models.forward_tts import ForwardTTS
@@ -83,7 +83,7 @@ model = ForwardTTS(config, ap, tokenizer, speaker_manager)
 # Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
 # distributed training, etc.
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 
 # AND... 3,2,1... 🚀

recipes/vctk/tacotron-DDC/train_tacotron-DDC.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config.shared_configs import BaseAudioConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.shared_configs import BaseDatasetConfig
 from TTS.tts.configs.tacotron_config import TacotronConfig
 from TTS.tts.datasets import load_tts_samples
@@ -85,7 +85,7 @@ model = Tacotron(config, ap, tokenizer, speaker_manager)
 # Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
 # distributed training, etc.
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 
 # AND... 3,2,1... 🚀

recipes/vctk/tacotron2-DDC/train_tacotron2-ddc.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config.shared_configs import BaseAudioConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.shared_configs import BaseDatasetConfig
 from TTS.tts.configs.tacotron2_config import Tacotron2Config
 from TTS.tts.datasets import load_tts_samples
@@ -91,7 +91,7 @@ model = Tacotron2(config, ap, tokenizer, speaker_manager)
 # Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
 # distributed training, etc.
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 
 # AND... 3,2,1... 🚀

recipes/vctk/tacotron2/train_tacotron2.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config.shared_configs import BaseAudioConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.shared_configs import BaseDatasetConfig
 from TTS.tts.configs.tacotron2_config import Tacotron2Config
 from TTS.tts.datasets import load_tts_samples
@@ -91,7 +91,7 @@ model = Tacotron2(config, ap, tokenizer, speaker_manager)
 # Trainer provides a generic API to train all the 🐸TTS models with all its perks like mixed-precision training,
 # distributed training, etc.
 trainer = Trainer(
-    TrainingArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
+    TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
 )
 
 # AND... 3,2,1... 🚀

recipes/vctk/vits/train_vits.py

@@ -1,7 +1,7 @@
 import os
 
 from TTS.config.shared_configs import BaseAudioConfig
-from TTS.trainer import Trainer, TrainingArgs
+from trainer import Trainer, TrainerArgs
 from TTS.tts.configs.shared_configs import BaseDatasetConfig
 from TTS.tts.configs.vits_config import VitsConfig
 from TTS.tts.datasets import load_tts_samples
@@ -90,7 +90,7 @@ model = Vits(config, ap, tokenizer, speaker_manager)
 
 # init the trainer and 🚀
 trainer = Trainer(
-    TrainingArgs(),
+    TrainerArgs(),
     config,
     output_path,
     model=model,